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Comparing Time‐Series and Survey Forecasts of Weekly Changes in Money: A Methodological Note
Author(s) -
HAFER R. W.
Publication year - 1984
Publication title -
the journal of finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 18.151
H-Index - 299
eISSN - 1540-6261
pISSN - 0022-1082
DOI - 10.1111/j.1540-6261.1984.tb03904.x
Subject(s) - citation , library science , computer science
measured as the difference between the announced change and the expected change derived from the Money Market Services, Inc. weekly survey of government securities dealers. Unlike other survey measures of expectations (the most notable example of which is the Livingston survey data), these expectations are formed by active market participants.' Consequently, the survey's forecast, made public before the Fed's announcement of the actual change in the money stock, is commonly thought to represent the "market's" expectation. The concern in this paper is not with the impact of unanticipated money changes on nominal interest rates. The purpose is to compare the relative forecasting abilities of the survey predictions and those obtained from a timeseries model. This question is of interest, because the weekly money series used in previous research includes certain "abnormal" weeks in which exogenous factors may significantly alter the series' stochastic properties (see, for example, Cornell [1], Urich and Wachtel [9]). Thus, the influence of these abnormal weeks-weeks that include benchmark revisions, changes in seasonal factors, and weeks in which there is a "social security effect"-is examined by comparing forecasting results for two samples; one includes these weeks and the other deletes them. Following Pearce [6], this approach allows us to test the hypothesis that the survey responses are at least weak-form rational and to see how sensitive this test is to the sample of weeks used. Unlike previous studies, we use two survey forecast series: the median forecast, made public prior to the announced change in Ml, and the mean series, constructed from individual respondents' forecasts. Zarnowitz's [10] examination of the ASA-NBER survey forecasts indicates that the mean forecast is, on average, statistically superior to the median. This finding is based on the idea that the mean forecast uses a more informationally diverse data set. Consequently, it is